The global properties of vascular networks grown with an in vitro angiogenesis assay are compared quantitatively, using automated image analysis, with the global properties of networks obtained with discrete, stochastic growth models. The model classes that are investigated are invasion percolation and diffusion limited aggregation. By matching global properties to experimental data, one can infer which model classes and parameters are most reflective of angiogenesis in experimental cells. This sheds light on large-scale emergent properties of angiogenesis from a systems perspective. It is found that invasion percolation is better than diffusion limited aggregation at matching experimental data. We also present evidence that the distribution of the lengths of real tubule complexes follows a power law.